Network fabric's measurement tools have been widely explored over the past several years. The most important characteristics of a network fabric are network topology, bandwidth, and latency. Measurement of such characteristics of a network is important for network troubleshooting and optimization of network applications such as end-to-end transport performance, intelligent overlay network routing, and peer-to-peer file distribution.
There are quite a few tools that are currently used to estimate bandwidths of hop-by-hop links or end-to-end paths in a network. However, with recent evolution in network technology, network topologies have become more and more complex. For example, in recent years, Equal-Cost Multi-Path (ECMP) Internet Protocol (IP) routing has been widely deployed to implement load balancing in the networks. The ECMP routing potentially offers substantial increases in bandwidth of the network by load-balancing the network traffic over multiple paths. For such networks, the current measurement tools can only estimate the bandwidth for a single random path.
There are also multiple paths discovery tools that are currently used to detect multiple paths between a given Internet Protocol (IP) endpoints pair in networks that deploy load balancing forwarding elements (e.g., load balancing routers). These tools, however, have their own shortcomings. For example, most available network path discovery tools (e.g., traceroute) can only discover a limited number of paths (e.g., three paths) in best-case scenario. Additionally, there is always the possibility that these tools fail to discover true nodes and links in a network or worse yet, introduce false links that in reality don't exist in the network.
For data center networks, the aforementioned network characteristics are rarely explored and those network fabrics are mostly treated as high-capacity black boxes. However, with the evolution of Software-Defined Data Centers (SDDC), more and more aspects of the infrastructure of the network are abstracted and built on top of the network fabric, and understanding network fabric characteristics has become crucial for planning, monitoring, and troubleshooting of the networks.